Now showing items 1-5 of 5

    • A Data and Platform-Aware Framework For Large-Scale Machine Learning 

      Mirhoseini, Azalia (2015-04-24)
      This thesis introduces a novel framework for execution of a broad class of iterative machine learning algorithms on massive and dense (non-sparse) datasets. Several classes of critical and fast-growing data, including image ...
    • Mining Massive-Scale Time Series Data using Hashing 

      Luo, Chen (2017-05-09)
      Similarity search on time series is a frequent operation in large-scale data-driven applications. Sophisticated similarity measures are standard for time series matching, as they are usually misaligned. Dynamic Time Warping ...
    • oASIS: Adaptive Column Sampling for Kernel Matrix Approximation 

      Patel, Raajen (2015-04-21)
      Kernel or similarity matrices are essential for many state-of-the-art approaches to classification, clustering, and dimensionality reduction. For large datasets, the cost of forming and factoring such kernel matrices becomes ...
    • Predicting Tissue Characteristics in Brain Tumors Using Radiological-Pathological Correlations 

      Lin, Jonathan Sunwei (2016-08-26)
      This thesis describes the development of prediction techniques for tissue characteristics in brain tumors, using both imaging and tissue information. Magnetic resonance imaging (MRI) serves as an aid in the clinical ...
    • Synthesis of Patient Data to Predict Outcomes 

      Myers, Risa B (2016-04-21)
      Healthcare data is increasingly collected and stored in electronic format, providing access to previously untapped information. At the same time, healthcare costs continue to escalate. Predicting important outcomes such ...